Generating improved belief networks


Ontology type: sgo:Patent     


Patent Info

DATE

2003-03-04T00:00

AUTHORS

David E. Heckerman , Dan Geiger , David M. Chickering

ABSTRACT

An improved belief network generator is provided. A belief network is generated utilizing expert knowledge retrieved from an expert in a given field of expertise and empirical data reflecting observations made in the given field of the expert. In addition to utilizing expert knowledge and empirical data, the belief network generator provides for the use of continuous variables in the generated belief network and missing data in the empirical data. More... »

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/2746", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "name": "David E. Heckerman", 
        "type": "Person"
      }, 
      {
        "name": "Dan Geiger", 
        "type": "Person"
      }, 
      {
        "name": "David M. Chickering", 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "sg:pub.10.1007/bf00994110", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1046316965", 
          "https://doi.org/10.1007/bf00994110"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1049/ip-i-2.1993.0008", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1056855628"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/34.204903", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061155783"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/49.257935", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061176920"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1109/64.295137", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1061205010"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1214/ss/1177010888", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064409646"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2003-03-04T00:00", 
    "description": "

An improved belief network generator is provided. A belief network is generated utilizing expert knowledge retrieved from an expert in a given field of expertise and empirical data reflecting observations made in the given field of the expert. In addition to utilizing expert knowledge and empirical data, the belief network generator provides for the use of continuous variables in the generated belief network and missing data in the empirical data.

", "id": "sg:patent.US-6529888-B1", "keywords": [ "belief network", "expert knowledge", "expert", "given field", "expertise", "empirical data", "observation", "continuous variable" ], "name": "Generating improved belief networks", "recipient": [ { "id": "https://www.grid.ac/institutes/grid.419815.0", "type": "Organization" } ], "sameAs": [ "https://app.dimensions.ai/details/patent/US-6529888-B1" ], "sdDataset": "patents", "sdDatePublished": "2019-04-18T10:28", "sdLicense": "https://scigraph.springernature.com/explorer/license/", "sdPublisher": { "name": "Springer Nature - SN SciGraph project", "type": "Organization" }, "sdSource": "s3://com-uberresearch-data-patents-target-20190320-rc/data/sn-export/402f166718b70575fb5d4ffe01f064d1/0000100128-0000352499/json_export_03120.jsonl", "type": "Patent" } ]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/patent.US-6529888-B1'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/patent.US-6529888-B1'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/patent.US-6529888-B1'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/patent.US-6529888-B1'


 

This table displays all metadata directly associated to this object as RDF triples.

57 TRIPLES      15 PREDICATES      28 URIs      16 LITERALS      2 BLANK NODES

Subject Predicate Object
1 sg:patent.US-6529888-B1 schema:about anzsrc-for:2746
2 schema:author N2a3f5df95a8446b488d1b0ef290380e0
3 schema:citation sg:pub.10.1007/bf00994110
4 https://doi.org/10.1049/ip-i-2.1993.0008
5 https://doi.org/10.1109/34.204903
6 https://doi.org/10.1109/49.257935
7 https://doi.org/10.1109/64.295137
8 https://doi.org/10.1214/ss/1177010888
9 schema:datePublished 2003-03-04T00:00
10 schema:description <p>An improved belief network generator is provided. A belief network is generated utilizing expert knowledge retrieved from an expert in a given field of expertise and empirical data reflecting observations made in the given field of the expert. In addition to utilizing expert knowledge and empirical data, the belief network generator provides for the use of continuous variables in the generated belief network and missing data in the empirical data.</p>
11 schema:keywords belief network
12 continuous variable
13 empirical data
14 expert
15 expert knowledge
16 expertise
17 given field
18 observation
19 schema:name Generating improved belief networks
20 schema:recipient https://www.grid.ac/institutes/grid.419815.0
21 schema:sameAs https://app.dimensions.ai/details/patent/US-6529888-B1
22 schema:sdDatePublished 2019-04-18T10:28
23 schema:sdLicense https://scigraph.springernature.com/explorer/license/
24 schema:sdPublisher Nab8220637ce84159b4deb5c14c95b8af
25 sgo:license sg:explorer/license/
26 sgo:sdDataset patents
27 rdf:type sgo:Patent
28 N1b0900c8abbf422596951e6c9100d483 schema:name David E. Heckerman
29 rdf:type schema:Person
30 N2a3f5df95a8446b488d1b0ef290380e0 rdf:first N1b0900c8abbf422596951e6c9100d483
31 rdf:rest Ndd359000a5fe4e9ea8cd9e050736ef3b
32 Nab8220637ce84159b4deb5c14c95b8af schema:name Springer Nature - SN SciGraph project
33 rdf:type schema:Organization
34 Nc9b519dd1dae4027bf7985a94c962854 schema:name Dan Geiger
35 rdf:type schema:Person
36 Ndd359000a5fe4e9ea8cd9e050736ef3b rdf:first Nc9b519dd1dae4027bf7985a94c962854
37 rdf:rest Ne3a9b219cb2847b5bc9b26e0edfabad7
38 Ne3a9b219cb2847b5bc9b26e0edfabad7 rdf:first Nf562212f44824a7eb84e21c4d4c3e515
39 rdf:rest rdf:nil
40 Nf562212f44824a7eb84e21c4d4c3e515 schema:name David M. Chickering
41 rdf:type schema:Person
42 anzsrc-for:2746 schema:inDefinedTermSet anzsrc-for:
43 rdf:type schema:DefinedTerm
44 sg:pub.10.1007/bf00994110 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046316965
45 https://doi.org/10.1007/bf00994110
46 rdf:type schema:CreativeWork
47 https://doi.org/10.1049/ip-i-2.1993.0008 schema:sameAs https://app.dimensions.ai/details/publication/pub.1056855628
48 rdf:type schema:CreativeWork
49 https://doi.org/10.1109/34.204903 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061155783
50 rdf:type schema:CreativeWork
51 https://doi.org/10.1109/49.257935 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061176920
52 rdf:type schema:CreativeWork
53 https://doi.org/10.1109/64.295137 schema:sameAs https://app.dimensions.ai/details/publication/pub.1061205010
54 rdf:type schema:CreativeWork
55 https://doi.org/10.1214/ss/1177010888 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064409646
56 rdf:type schema:CreativeWork
57 https://www.grid.ac/institutes/grid.419815.0 schema:Organization
 




Preview window. Press ESC to close (or click here)


...